
// g++ -O3 -g0 -DNDEBUG  sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.005 -DSIZE=10000 && ./a.out
// g++ -O3 -g0 -DNDEBUG  sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.05 -DSIZE=2000 && ./a.out
//  -DNOGMM -DNOMTL
//  -I /home/gael/Coding/LinearAlgebra/CSparse/Include/ /home/gael/Coding/LinearAlgebra/CSparse/Lib/libcsparse.a

#ifndef SIZE
#    define SIZE 10000
#endif

#ifndef DENSITY
#    define DENSITY 0.01
#endif

#ifndef REPEAT
#    define REPEAT 1
#endif

#include "BenchSparseUtil.h"

#ifndef MINDENSITY
#    define MINDENSITY 0.0004
#endif

#ifndef NBTRIES
#    define NBTRIES 10
#endif

#define BENCH(X)                                \
    timer.reset();                              \
    for ( int _j = 0; _j < NBTRIES; ++_j ) {    \
        timer.start();                          \
        for ( int _k = 0; _k < REPEAT; ++_k ) { \
            X                                   \
        }                                       \
        timer.stop();                           \
    }

typedef SparseMatrix<Scalar, UpperTriangular>               EigenSparseTriMatrix;
typedef SparseMatrix<Scalar, RowMajorBit | UpperTriangular> EigenSparseTriMatrixRow;

void fillMatrix(float density, int rows, int cols, EigenSparseTriMatrix& dst)
{
    dst.startFill(rows * cols * density);
    for ( int j = 0; j < cols; j++ ) {
        for ( int i = 0; i < j; i++ ) {
            Scalar v = (internal::random<float>(0, 1) < density) ? internal::random<Scalar>() : 0;
            if ( v != 0 )
                dst.fill(i, j) = v;
        }
        dst.fill(j, j) = internal::random<Scalar>();
    }
    dst.endFill();
}

int main(int argc, char* argv[])
{
    int        rows    = SIZE;
    int        cols    = SIZE;
    float      density = DENSITY;
    BenchTimer timer;
#if 1
    EigenSparseTriMatrix               sm1(rows, cols);
    typedef Matrix<Scalar, Dynamic, 1> DenseVector;
    DenseVector                        b = DenseVector::Random(cols);
    DenseVector                        x = DenseVector::Random(cols);

    bool densedone = false;

    for ( float density = DENSITY; density >= MINDENSITY; density *= 0.5 ) {
        EigenSparseTriMatrix sm1(rows, cols);
        fillMatrix(density, rows, cols, sm1);

// dense matrices
#    ifdef DENSEMATRIX
        if ( !densedone ) {
            densedone = true;
            std::cout << "Eigen Dense\t" << density * 100 << "%\n";
            DenseMatrix                                                     m1(rows, cols);
            Matrix<Scalar, Dynamic, Dynamic, Dynamic, Dynamic, RowMajorBit> m2(rows, cols);
            eiToDense(sm1, m1);
            m2 = m1;

            BENCH(x = m1.marked<UpperTriangular>().solveTriangular(b);)
            std::cout << "   colmajor^-1 * b:\t" << timer.value() << endl;
            //       std::cerr << x.transpose() << "\n";

            BENCH(x = m2.marked<UpperTriangular>().solveTriangular(b);)
            std::cout << "   rowmajor^-1 * b:\t" << timer.value() << endl;
            //       std::cerr << x.transpose() << "\n";
        }
#    endif

        // eigen3 sparse matrices
        {
            std::cout << "Eigen sparse\t" << density * 100 << "%\n";
            EigenSparseTriMatrixRow sm2 = sm1;

            BENCH(x = sm1.solveTriangular(b);)
            std::cout << "   colmajor^-1 * b:\t" << timer.value() << endl;
            //       std::cerr << x.transpose() << "\n";

            BENCH(x = sm2.solveTriangular(b);)
            std::cout << "   rowmajor^-1 * b:\t" << timer.value() << endl;
            //       std::cerr << x.transpose() << "\n";

            //       x = b;
            //       BENCH(sm1.inverseProductInPlace(x);)
            //       std::cout << "   colmajor^-1 * b:\t" << timer.value() << " (inplace)" << endl;
            //       std::cerr << x.transpose() << "\n";
            //
            //       x = b;
            //       BENCH(sm2.inverseProductInPlace(x);)
            //       std::cout << "   rowmajor^-1 * b:\t" << timer.value() << " (inplace)" << endl;
            //       std::cerr << x.transpose() << "\n";
        }



// CSparse
#    ifdef CSPARSE
        {
            std::cout << "CSparse \t" << density * 100 << "%\n";
            cs* m1;
            eiToCSparse(sm1, m1);

            BENCH(x = b; if ( !cs_lsolve(m1, x.data()) ) {std::cerr << "cs_lsolve failed\n"; break; };)
            std::cout << "   colmajor^-1 * b:\t" << timer.value() << endl;
        }
#    endif

// GMM++
#    ifndef NOGMM
        {
            std::cout << "GMM++ sparse\t" << density * 100 << "%\n";
            GmmSparse               m1(rows, cols);
            gmm::csr_matrix<Scalar> m2;
            eiToGmm(sm1, m1);
            gmm::copy(m1, m2);
            std::vector<Scalar> gmmX(cols), gmmB(cols);
            Map<Matrix<Scalar, Dynamic, 1>>(&gmmX[0], cols) = x;
            Map<Matrix<Scalar, Dynamic, 1>>(&gmmB[0], cols) = b;

            gmmX = gmmB;
            BENCH(gmm::upper_tri_solve(m1, gmmX, false);)
            std::cout << "   colmajor^-1 * b:\t" << timer.value() << endl;
            //       std::cerr << Map<Matrix<Scalar,Dynamic,1> >(&gmmX[0], cols).transpose() << "\n";

            gmmX = gmmB;
            BENCH(gmm::upper_tri_solve(m2, gmmX, false);)
            timer.stop();
            std::cout << "   rowmajor^-1 * b:\t" << timer.value() << endl;
            //       std::cerr << Map<Matrix<Scalar,Dynamic,1> >(&gmmX[0], cols).transpose() << "\n";
        }
#    endif

// MTL4
#    ifndef NOMTL
        {
            std::cout << "MTL4\t" << density * 100 << "%\n";
            MtlSparse         m1(rows, cols);
            MtlSparseRowMajor m2(rows, cols);
            eiToMtl(sm1, m1);
            m2 = m1;
            mtl::dense_vector<Scalar> x(rows, 1.0);
            mtl::dense_vector<Scalar> b(rows, 1.0);

            BENCH(x = mtl::upper_trisolve(m1, b);)
            std::cout << "   colmajor^-1 * b:\t" << timer.value() << endl;
            //       std::cerr << x << "\n";

            BENCH(x = mtl::upper_trisolve(m2, b);)
            std::cout << "   rowmajor^-1 * b:\t" << timer.value() << endl;
            //       std::cerr << x << "\n";
        }
#    endif


        std::cout << "\n\n";
    }
#endif

#if 0
    // bench small matrices (in-place versus return bye value)
    {
      timer.reset();
      for (int _j=0; _j<10; ++_j) {
        Matrix4f m = Matrix4f::Random();
        Vector4f b = Vector4f::Random();
        Vector4f x = Vector4f::Random();
        timer.start();
        for (int _k=0; _k<1000000; ++_k) {
          b = m.inverseProduct(b);
        }
        timer.stop();
      }
      std::cout << "4x4 :\t" << timer.value() << endl;
    }

    {
      timer.reset();
      for (int _j=0; _j<10; ++_j) {
        Matrix4f m = Matrix4f::Random();
        Vector4f b = Vector4f::Random();
        Vector4f x = Vector4f::Random();
        timer.start();
        for (int _k=0; _k<1000000; ++_k) {
          m.inverseProductInPlace(x);
        }
        timer.stop();
      }
      std::cout << "4x4 IP :\t" << timer.value() << endl;
    }
#endif

    return 0;
}
